CDSimX-introduction
Introduction
The CDSimX package provides an advanced framework for climate simulation, forecasting, visualization, validation, and climate data export in R.
The package supports:
synthetic weather station generation
stochastic climate simulation
machine learning forecasting
climate validation
NetCDF and CSV export
visualization of climate variables
climate dependence modelling
CDSimX is useful for:
climate research
hydrological modelling
machine learning experiments
educational demonstrations
sensitivity analysis
simulation studies
Creating Weather Stations
The stations can be created either by: loading from a CSV file, accepting an existing data frame, or auto-generating synthetic stations in a bounding box. We begin by generating synthetic climate stations.
stations <- create_stations(
n = 3,
seed = 123
)
#> Generating synthetic station network...
#> Generated 3 synthetic stations within bounding box.
#> Deriving climate-aware station attributes...
stations
#> Station LON LAT ELEV CLIMATE_ZONE COASTAL_INDEX TEMP_BASE
#> 1 Station_1 -2.0621124 10.681122 422.5 Savannah 0.932 27.17
#> 2 Station_2 0.4415257 11.083271 713.9 Savannah 1.000 26.27
#> 3 Station_3 -1.4551154 4.818895 441.1 Coastal 0.000 27.04
#> RAIN_REGIME
#> 1 Monomodal
#> 2 Monomodal
#> 3 BimodalEach station contains:
station identifier
longitude
latitude
elevation (if available)
Generating Time Indices
CDSimX supports daily, monthly, and yearly temporal resolutions.
time_index <- generate_time_index(
start_date = "2019-01-01",
end_date = "2024-12-31",
frequency = "day"
)
#> Generated 2192 time steps at daily resolution.
head(time_index)
#> START_DATE END_DATE DATE Year Month Day DOY Week Quarter Season
#> 1 2019-01-01 2019-01-01 2019-01-01 2019 1 1 1 1 1 Dry
#> 2 2019-01-02 2019-01-02 2019-01-02 2019 1 2 2 1 1 Dry
#> 3 2019-01-03 2019-01-03 2019-01-03 2019 1 3 3 1 1 Dry
#> 4 2019-01-04 2019-01-04 2019-01-04 2019 1 4 4 1 1 Dry
#> 5 2019-01-05 2019-01-05 2019-01-05 2019 1 5 5 1 1 Dry
#> 6 2019-01-06 2019-01-06 2019-01-06 2019 1 6 6 1 1 Dry
#> Frequency
#> 1 daily
#> 2 daily
#> 3 daily
#> 4 daily
#> 5 daily
#> 6 dailySimulating Climate Data
Climate variables can now be simulated using the generated stations and time index.
climate <- simulate_climate(
stations = stations,
time_index = time_index,
seed = 123
)
#> Temperature simulation complete for 3 stations.
#> Rainfall simulation complete for 3 stations.
#> Relative humidity simulation complete for 3 stations.
#> Dew point simulation complete for 3 stations.
#> Wind speed simulation complete for 3 stations.
#> Wind direction simulation complete for 3 stations.
#> Solar radiation simulation complete for 3 stations.
#> Evapotranspiration simulation complete for 3 stations.
#> Integrated climate simulation complete for 3 stations.
head(climate)
#> Station DATE LON LAT ELEV Year Month Season Tmin Tmax
#> 1 Station_1 2019-01-01 -2.062112 10.68112 422.5 2019 1 Dry 20.31 28.03
#> 2 Station_1 2019-01-02 -2.062112 10.68112 422.5 2019 1 Dry 20.21 28.64
#> 3 Station_1 2019-01-03 -2.062112 10.68112 422.5 2019 1 Dry 21.91 29.66
#> 4 Station_1 2019-01-04 -2.062112 10.68112 422.5 2019 1 Dry 21.96 30.36
#> 5 Station_1 2019-01-05 -2.062112 10.68112 422.5 2019 1 Dry 22.07 30.95
#> 6 Station_1 2019-01-06 -2.062112 10.68112 422.5 2019 1 Dry 23.76 32.02
#> Avg.Temp DTR CLIMATE_ZONE COASTAL_INDEX Rain_Days Rainfall Wet_Day
#> 1 24.17 7.72 Savannah 0.932 0 0.00 0
#> 2 24.42 8.43 Savannah 0.932 0 0.00 0
#> 3 25.78 7.75 Savannah 0.932 0 0.00 0
#> 4 26.16 8.41 Savannah 0.932 1 0.84 1
#> 5 26.51 8.88 Savannah 0.932 0 0.00 0
#> 6 27.89 8.26 Savannah 0.932 0 0.00 0
#> Extreme_Event Rain_Anomaly RH Humidity_Anomaly DewPoint
#> 1 0 -1.08 53.05 -5.07 13.35
#> 2 0 -1.08 52.75 -5.37 14.20
#> 3 0 -1.08 57.88 -0.23 16.23
#> 4 0 -0.24 58.04 -0.07 17.29
#> 5 0 -1.08 57.92 -0.19 18.05
#> 6 0 -1.08 62.81 4.70 20.03
#> Dewpoint_Depression WindSpeed Extreme_Wind Wind_Anomaly WindDirection
#> 1 10.82 3.45 0 -3.87 148.59
#> 2 10.22 5.44 0 -1.87 140.34
#> 3 9.55 5.98 0 -1.34 240.74
#> 4 8.87 7.78 0 0.46 234.74
#> 5 8.46 9.15 0 1.84 231.49
#> 6 7.86 9.67 0 2.35 276.37
#> WindSector Prevailing_Direction Direction_Variability Extreme_Shift Wind_u
#> 1 SE 180 60 0 -1.80
#> 2 SE 180 60 0 -3.47
#> 3 SW 180 60 0 5.22
#> 4 SW 180 30 0 6.35
#> 5 SW 180 30 0 7.16
#> 6 W 180 30 0 9.61
#> Wind_v Solar_Radiation Clear_Sky_Radiation Cloud_Factor Sunshine_Fraction
#> 1 2.94 16.31 21.04 0.85 0.8739915
#> 2 4.19 21.47 21.07 0.93 0.9212083
#> 3 2.92 18.10 21.09 0.87 0.8337447
#> 4 4.49 17.12 21.12 0.93 0.8956804
#> 5 5.70 22.41 21.15 0.94 0.9298279
#> 6 -1.07 16.35 21.18 0.81 0.8450011
#> Radiation_Anomaly Atmospheric_Pressure VPD ET0 Dryness_Index Dryness_Class
#> 1 -3.08 96.4 1.42 5.88 0.82 Very Dry
#> 2 2.08 96.4 1.45 6.78 0.64 Very Dry
#> 3 -1.29 96.4 1.40 7.05 0.73 Very Dry
#> 4 -2.27 96.4 1.42 6.77 0.79 Very Dry
#> 5 3.02 96.4 1.46 7.58 0.62 Very Dry
#> 6 -3.04 96.4 1.40 7.48 0.81 Very Dry
#> ET_Anomaly
#> 1 -1.20
#> 2 -0.30
#> 3 -0.03
#> 4 -0.31
#> 5 0.50
#> 6 0.40The simulated dataset may include:
Tmin
Tmax
Rainfall
RH
WindSpeed
Solar_Radiation
ET0
DewPoint
Climate Visualization
CDSimX includes customizable visualization functions.
plot_station_timeseries(
climate,
station = "Station_1",
var = "Tmax"
)
#> `geom_smooth()` using formula = 'y ~ x'
Users may customize:
colors
themes
smoothing
labels
seasonal highlighting
Machine Learning Forecasting
CDSimX supports several machine learning forecasting approaches.
Available methods include:
Random Forest
Linear Regression
GBM
ARIMA
XGBoost
Neural Networks
forecast_result <- forecasting_ml(
climate_data = climate,
target = "Rainfall",
forecast_horizon = 12,
method = "rf"
)
#> Machine learning forecasting complete using rf method.
forecast_result$model_performance
#> Method Target RMSE MAE Correlation
#> 1 rf Rainfall 44.99 35.08 0.39Forecasted values:
head(forecast_result$forecast_data)
#> DATE Forecast
#> 1 2025-01-31 34.17
#> 2 2025-03-03 27.68
#> 3 2025-03-31 42.91
#> 4 2025-05-01 16.10
#> 5 2025-05-31 38.05
#> 6 2025-07-01 47.99Climate Validation
CDSimX includes climate validation tools for checking realism and statistical consistency.
validation <- validate_climate(climate)
#> Climate dataset validation complete.
validation
#> $summary_statistics
#> Variable Mean SD Min Max Skewness
#> 1 LON -1.03 1.07 -2.06 0.44 0.54
#> 2 LAT 8.86 2.86 4.82 11.08 -0.70
#> 3 ELEV 525.83 133.21 422.50 713.90 0.70
#> 4 Year 2021.50 1.71 2019.00 2024.00 0.00
#> 5 Month 6.52 3.45 1.00 12.00 -0.01
#> 6 Tmin 20.36 3.55 10.03 30.19 -0.23
#> 7 Tmax 26.90 3.75 15.74 38.67 0.35
#> 8 Avg.Temp 23.63 3.46 13.60 34.36 0.10
#> 9 DTR 6.54 2.33 1.79 10.29 -0.64
#> 10 COASTAL_INDEX 0.64 0.46 0.00 1.00 -0.70
#> 11 Rain_Days 0.42 0.49 0.00 1.00 0.31
#> 12 Rainfall 21.69 37.45 0.00 429.86 2.36
#> 13 Wet_Day 0.42 0.49 0.00 1.00 0.31
#> 14 Extreme_Event 0.01 0.08 0.00 1.00 11.83
#> 15 Rain_Anomaly 0.00 32.88 -69.56 381.95 1.84
#> 16 RH 64.34 17.59 29.97 100.00 0.47
#> 17 Humidity_Anomaly 0.00 5.42 -19.15 19.99 -0.07
#> 18 DewPoint 16.03 6.36 -3.36 30.10 -0.33
#> 19 Dewpoint_Depression 7.60 4.14 0.00 17.23 -0.29
#> 20 WindSpeed 7.85 3.70 0.00 34.17 0.25
#> 21 Extreme_Wind 0.01 0.10 0.00 1.00 10.24
#> 22 Wind_Anomaly 0.00 2.89 -9.40 25.04 0.38
#> 23 WindDirection 187.24 78.26 0.21 359.89 -0.28
#> 24 Prevailing_Direction 195.00 21.21 180.00 225.00 0.71
#> 25 Direction_Variability 37.49 16.01 15.00 60.00 0.46
#> 26 Extreme_Shift 0.01 0.09 0.00 1.00 10.41
#> 27 Wind_u 2.46 6.14 -12.78 33.11 0.37
#> 28 Wind_v 3.10 4.68 -17.96 19.85 -0.62
#> 29 Solar_Radiation 20.99 2.48 12.61 29.50 0.04
#> 30 Clear_Sky_Radiation 24.55 1.59 20.90 26.83 -0.68
#> 31 Cloud_Factor 0.86 0.05 0.71 0.97 -0.08
#> 32 Sunshine_Fraction 0.85 0.06 0.64 1.00 -0.08
#> 33 Radiation_Anomaly 0.00 1.95 -6.91 6.27 0.01
#> 34 Atmospheric_Pressure 95.24 1.49 93.14 96.40 -0.70
#> 35 VPD 1.02 0.49 0.00 1.65 -0.75
#> 36 ET0 6.82 0.89 3.94 9.89 0.02
#> 37 Dryness_Index 0.47 0.22 0.00 0.98 -0.56
#> 38 ET_Anomaly 0.00 0.69 -2.66 2.64 0.01
#>
#> $missing_values
#> Variable Missing_Count Missing_Percent
#> Station Station 0 0
#> DATE DATE 0 0
#> LON LON 0 0
#> LAT LAT 0 0
#> ELEV ELEV 0 0
#> Year Year 0 0
#> Month Month 0 0
#> Season Season 0 0
#> Tmin Tmin 0 0
#> Tmax Tmax 0 0
#> Avg.Temp Avg.Temp 0 0
#> DTR DTR 0 0
#> CLIMATE_ZONE CLIMATE_ZONE 0 0
#> COASTAL_INDEX COASTAL_INDEX 0 0
#> Rain_Days Rain_Days 0 0
#> Rainfall Rainfall 0 0
#> Wet_Day Wet_Day 0 0
#> Extreme_Event Extreme_Event 0 0
#> Rain_Anomaly Rain_Anomaly 0 0
#> RH RH 0 0
#> Humidity_Anomaly Humidity_Anomaly 0 0
#> DewPoint DewPoint 0 0
#> Dewpoint_Depression Dewpoint_Depression 0 0
#> WindSpeed WindSpeed 0 0
#> Extreme_Wind Extreme_Wind 0 0
#> Wind_Anomaly Wind_Anomaly 0 0
#> WindDirection WindDirection 0 0
#> WindSector WindSector 0 0
#> Prevailing_Direction Prevailing_Direction 0 0
#> Direction_Variability Direction_Variability 0 0
#> Extreme_Shift Extreme_Shift 0 0
#> Wind_u Wind_u 0 0
#> Wind_v Wind_v 0 0
#> Solar_Radiation Solar_Radiation 0 0
#> Clear_Sky_Radiation Clear_Sky_Radiation 0 0
#> Cloud_Factor Cloud_Factor 0 0
#> Sunshine_Fraction Sunshine_Fraction 0 0
#> Radiation_Anomaly Radiation_Anomaly 0 0
#> Atmospheric_Pressure Atmospheric_Pressure 0 0
#> VPD VPD 0 0
#> ET0 ET0 0 0
#> Dryness_Index Dryness_Index 0 0
#> Dryness_Class Dryness_Class 0 0
#> ET_Anomaly ET_Anomaly 0 0
#>
#> $physical_checks
#> $physical_checks$Temperature_Inconsistency
#> [1] 0
#>
#> $physical_checks$RH_Out_Of_Bounds
#> [1] 0
#>
#> $physical_checks$Negative_Rainfall
#> [1] 0
#>
#> $physical_checks$Negative_WindSpeed
#> [1] 0
#>
#> $physical_checks$Invalid_WindDirection
#> [1] 0
#>
#> $physical_checks$Invalid_DewPoint
#> [1] 0
#>
#> $physical_checks$Invalid_SunshineFraction
#> [1] 0
#>
#> $physical_checks$Negative_ET0
#> [1] 0
#>
#>
#> $correlation_matrix
#> Tmin Tmax Avg.Temp Rainfall RH DewPoint WindSpeed
#> Tmin 1.00 0.80 0.95 -0.04 0.65 0.94 0.73
#> Tmax 0.80 1.00 0.95 -0.25 0.08 0.59 0.45
#> Avg.Temp 0.95 0.95 1.00 -0.15 0.38 0.80 0.61
#> Rainfall -0.04 -0.25 -0.15 1.00 0.28 0.10 0.11
#> RH 0.65 0.08 0.38 0.28 1.00 0.85 0.74
#> DewPoint 0.94 0.59 0.80 0.10 0.85 1.00 0.85
#> WindSpeed 0.73 0.45 0.61 0.11 0.74 0.85 1.00
#> Solar_Radiation 0.04 0.15 0.10 -0.19 -0.13 -0.03 -0.05
#> ET0 0.84 0.82 0.87 -0.13 0.40 0.75 0.73
#> Solar_Radiation ET0
#> Tmin 0.04 0.84
#> Tmax 0.15 0.82
#> Avg.Temp 0.10 0.87
#> Rainfall -0.19 -0.13
#> RH -0.13 0.40
#> DewPoint -0.03 0.75
#> WindSpeed -0.05 0.73
#> Solar_Radiation 1.00 0.37
#> ET0 0.37 1.00
#>
#> $seasonal_summary
#> Season Tmin Tmax Avg.Temp Rainfall RH DewPoint WindSpeed
#> 1 Dry 21.12 27.65 24.39 9.05 65.96 17.17 8.28
#> 2 Post-Wet 18.30 24.86 21.58 22.13 58.99 12.79 6.74
#> 3 Pre-Wet 22.83 29.37 26.10 15.98 70.55 19.91 9.36
#> 4 Wet 18.97 25.50 22.24 35.14 61.14 13.89 6.94
#> Solar_Radiation ET0
#> 1 19.83 6.82
#> 2 19.45 6.27
#> 3 22.48 7.46
#> 4 21.51 6.61
#>
#> $station_summary
#> Station Tmin Tmax Avg.Temp Rainfall RH DewPoint WindSpeed
#> 1 Station_1 21.00 29.37 25.19 11.60 55.31 15.49 6.42
#> 2 Station_2 18.36 26.28 22.32 13.59 51.17 11.64 6.72
#> 3 Station_3 21.72 25.05 23.38 39.89 86.55 20.96 10.40
#> Solar_Radiation ET0
#> 1 21.00 6.97
#> 2 21.67 6.66
#> 3 20.31 6.83
#>
#> $extreme_summary
#> Metric Value
#> 1 Extreme_Rainfall_Events 46
#> 2 Extreme_Wind_Events 61
#>
#> $validation_summary
#> Metric Value
#> 1 Mean_Tmin 20.36
#> 2 Mean_Tmax 26.90
#> 3 Mean_Temperature 23.63
#> 4 Mean_Rainfall 21.69
#> 5 Mean_RH 64.34
#> 6 Mean_WindSpeed 7.85
#> 7 Mean_SolarRadiation 20.99
#> 8 Mean_ET0 6.82Validation diagnostics may include:
physical constraint checks
variability assessment
correlations
temporal consistency
distributional diagnostics
Exporting Climate Data
Export to CSV
Export to NetCDF
These formats support interoperability with:
ncdf4
terra
stars
xarray
climate modelling workflows
Conclusion
CDSimX provides a modern climate simulation ecosystem for generating, forecasting, validating, visualizing, and exporting synthetic climate data.
The package is designed to support reproducible climate science, machine learning applications, and environmental modelling workflows.